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Jim Crutchfield: Structure or Noise?

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Jim Crutchfield: Structure or Noise?


Published 2008


Seminar given by Jim Crutchfield of the Complexity Sciences Center, UC Davis on October 15, 2008 for the Redwood Center for Theoretical Neuroscience at UC Berkeley.

Abstract.
I will show how theory building can naturally distinguish between regularity and randomness. Starting from basic modeling principles, using rate distortion theory and computational mechanics I'll argue for a general information-theoretic objective function that embodies a trade-off between a model's complexity and its predictive power. The family of solutions derived from this principle corresponds to a hierarchy of models. At each level of complexity, they achieve maximal predictive power, identifying a process's exact causal organization in the limit of optimal prediction. Examples show how theory building can profit from analyzing a process's causal compressibility, which is reflected in the optimal models' rate-distortion curve.


Run time About 65 minutes.
Producer Redwood Center for Theoretical Neuroscience
Audio/Visual sound, color

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